iflow-graphify

name	iflow-graphify
description	Rebuild the graphify knowledge graph (graphify-out/) by shelling out to `issue-flow graphify` or `graphify` directly.
disable-model-invocation	true
issue-flow-version	0.4.2a4

issue-flow — graph rebuild (/iflow-graphify)

Follow this skill to refresh the project's graphify knowledge graph — a stale graphify-out/ after a large refactor, or the initial graph after installing graphifyy.

Do not use this skill from /iflow-start, /iflow-close, or /iflow. /iflow-graphify is opt-in only.

Invoke: type iflow graphify in chat, or /iflow-graphify from the slash menu (iflow-graphify also works).

MODEL & EXECUTION DIRECTIVE

Profile: economy — Prioritize speed and token economy over deep reasoning.

In Cursor: use Auto or a fast model before invoking this step.

Keep scope tight to what this step requires.

Instructions

1. Prefer issue-flow graphify from the project root:

   issue-flow graphify
   

   With no extra args this runs graphify update <project> — AST-only, no LLM API key required, produces the full graphify-out/. To pick a different graphify subcommand, pass it as the first arg: issue-flow graphify extract (adds the slower semantic LLM pass for richer relationships — needs an API key), issue-flow graphify watch (live), issue-flow graphify cluster-only --no-viz, etc. Use -C <dir> to scan a project other than the current directory. Trailing flags pass through verbatim. Do not invent new wrapper flags.

2. Fallback to graphify directly when issue-flow is unavailable:

   graphify update .
   

   graphify is subcommand-based — graphify . on its own is not valid (graphify reports unknown command '.'). Always pick a subcommand: update for the no-LLM AST build, extract for the full semantic pass, watch for a long-running watcher, etc.

3. If graphify exits with "no LLM API key found", the user picked extract (or another semantic subcommand) without configuring a backend. Cursor's own LLM is not available to subprocesses, so graphify cannot reuse it. Suggest one of:

   • Set an API key for GEMINI_API_KEY / GOOGLE_API_KEY, ANTHROPIC_API_KEY, OPENAI_API_KEY, or MOONSHOT_API_KEY.
   • Run issue-flow graphify extract --backend ollama to use a local LLM via Ollama (requires Ollama installed with a model pulled).
   • Drop the extract arg and use the default issue-flow graphify (AST-only, no LLM).

4. Handle missing graphify gracefully. If the run reports graphify is not on PATH, do not retry blindly. Tell the user to install it once:

   uv tool install graphifyy   # recommended
   pipx install graphifyy
   pip install graphifyy
   

   graphifyy (double-y) is the official PyPI package; the CLI is still graphify. After installing, suggest issue-flow update so graphify cursor install registers the graphify Cursor skill alongside this one.

5. Verify and report.

   • Confirm graphify-out/graph.json, graphify-out/graph.html, and graphify-out/GRAPH_REPORT.md exist after a successful run.
   • Surface non-zero exit codes verbatim; do not silently retry.
   • When the user asks "what changed?", skim GRAPH_REPORT.md (god nodes, surprising connections) for a short summary.

Constraints

• Never auto-dispatch /iflow-graphify from another slash command. The user opts in explicitly.
• Never commit graphify-out/cost.json or graphify-out/manifest.json; they are local-only.
• Long-running modes (watch) keep the process alive; ask the user before launching them in an agent context.
• Forward extra arguments verbatim. Do not translate or rewrite graphify's flag set inside issue-flow.